Benchmarking Methods For Mapping Functional Connectivity In The Brain Zhenqi Liu Andrea I Luppi Justine Y Hansen Ye Ella Tian Andrew Zalesky B T Thomas Yeo Ben D Fulcher Bratislav Misic by Zhen-qi Liu & Andrea I. Luppi & Justine Y. Hansen & Ye Ella Tian & Andrew Zalesky & B. T. Thomas Yeo & Ben D. Fulcher & Bratislav Misic instant download after payment.

The networked architecture of the brain promotes synchrony among neuronal populations. These communication patterns can be mapped using functional imaging, yielding functional connectivity (FC) networks. While most studies use Pearson’s correlations by default, numerous pairwise interaction statistics exist in the scientifc literature. How does the organization of the FC matrix vary with the choice of pairwise statistic? Here we use a library of 239 pairwise statistics to benchmark canonical features of FC networks, including hub mapping, weight–distance trade-ofs, structure–function coupling, correspondence with other neurophysiological networks, individual fngerprinting and brain–behavior prediction. We fnd substantial quantitative and qualitative variation across FC methods. Measures such as covariance, precision and distance display multiple desirable properties, including correspondence with structural connectivity and the capacity to diferentiate individuals and predict individual diferences in behavior. Our report highlights how FC mapping can be optimized by tailoring pairwise statistics to specifc neurophysiological mechanisms and research questions.